Question

# please answer 1-3 year catch effort 1962 51.8 50.0567 1963 44.3 44.3 1964 48 44.54 1965...

 year catch effort 1962 51.8 50.0567 1963 44.3 44.3 1964 48 44.54 1965 44.826 59.9788 1966 39.208 45.3769 1967 48.278 46.6083 1968 37.819 52.2453 1969 31.992 54.1197 1970 29.894 35.6082 1971 39.406 61.2475 1972 34.279 54.7616 1973 27.958 46.5664 1974 36.407 28.5148 1975 27.827 27.1653 1976 33.71 38.8333 1977 32.888 22.0711 1978 35.804 31.362 1979 38.95 25.6873 1980 29.157 19.38 1981 23.748 21.7888 1982 28.333 20.1047 1983 31.945 27.1808 1984 18.434 17.9237 1985 22.531 18.9703 1986 25.587 22.3778 1987 29.777 16.8984 1988 27.906 20.1961 1989 25.757 16.4284 1990 24.503 15.5728 1991 16.608 17.144 1992 18.162 15.7857 1993 18.371 12.1206 1994 16.993 10.3118

ARE 106

Quantitative Methods

Problem Set 3

The data set “BasqueTuna.dat” on Smartsite provides information on the total catch of white tuna in the Basque region of Spain (in tons) and the effort, or total days of fishing (in thousands) to produce this tuna, each year from 1962-1994.

1. Use the data to estimate a simple regression equation of the following form:

catcht  = b0  +b1effortt + et

Report your findings in either table or equation form. Does this regression satisfy CR3? Please show and explain your test for serial correlation at the 95% significance level. Present your results and explain your conclusion

2. Please specify and estimate a better regression model that you can defend, on the basis of economic theory, to explain the production of tuna as a function of effort. Explain why this functional form is better. Present and interpret your results. What is the elasticity of output with respect to effort in this new model?

3. Is serial correlation a problem with the model in (2)?  Please carefully present the results of your test for serial correlation (use the 95% significance level), present your results, and explain your findings.

4. Now re-estimate the model in (2) using the Newey-West method. Report your results and compare them with what you got in (2). What is different, and why?

5. Is there evidence that the marginal product of effort has changed over time?  How? Please show your work, explaining how you test for this and what you find.

6. Does the model in (5) exhibit serial correlation? Please test for this at the 95% level

and present your test results. Is the result different than in (3)? Please speculate on why or why not.

2

The simple linear regression model is

In our case

y= Dependent variable=Catch

x= Independent variable=Effort

Therefore the model is

After fitting the regression model we get,

 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 16.8113996 2.478641652 6.782505 1.353E-07 11.7561766 21.86662 11.7561766 21.866623 X Variable 1 0.46712366 0.070758985 6.601616 2.243E-07 0.32280976 0.611438 0.32280976 0.6114376

From the above information we get,

It can be interpreted as follow:

If the effort increase by one unit,the catch is also increase by 0.4671236 unit.

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